{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据预处理\n",
    "### 列重命名\n",
    "将“Unnamed: 0”列命名为“No”。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#读取训练集和测试集\n",
    "train = pd.read_csv('data\\cs-training.csv')\n",
    "test = pd.read_csv('data\\cs-test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#列重命名\n",
    "train.rename(columns={'Unnamed: 0':'No'}, inplace=True)\n",
    "test.rename(columns={'Unnamed: 0':'No'}, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 填充空值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先查看每个特征下的空值情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No                                          0\n",
       "SeriousDlqin2yrs                            0\n",
       "RevolvingUtilizationOfUnsecuredLines        0\n",
       "age                                         0\n",
       "NumberOfTime30-59DaysPastDueNotWorse        0\n",
       "DebtRatio                                   0\n",
       "MonthlyIncome                           29731\n",
       "NumberOfOpenCreditLinesAndLoans             0\n",
       "NumberOfTimes90DaysLate                     0\n",
       "NumberRealEstateLoansOrLines                0\n",
       "NumberOfTime60-89DaysPastDueNotWorse        0\n",
       "NumberOfDependents                       3924\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_values_count = train.isnull().sum()\n",
    "missing_values_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No                                           0\n",
       "SeriousDlqin2yrs                        101503\n",
       "RevolvingUtilizationOfUnsecuredLines         0\n",
       "age                                          0\n",
       "NumberOfTime30-59DaysPastDueNotWorse         0\n",
       "DebtRatio                                    0\n",
       "MonthlyIncome                            20103\n",
       "NumberOfOpenCreditLinesAndLoans              0\n",
       "NumberOfTimes90DaysLate                      0\n",
       "NumberRealEstateLoansOrLines                 0\n",
       "NumberOfTime60-89DaysPastDueNotWorse         0\n",
       "NumberOfDependents                        2626\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_values_count = test.isnull().sum()\n",
    "missing_values_count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "发现月收入和家庭成员数目特征都有着大量的空值。对月收入进行分析，对比退休和未退休人群的平均收入情况："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6664.144196724307, 6686.5059913187015)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "working_train = train.loc[(train['age'] >= 18) & (train['age'] <= 60)]\n",
    "retired_train = train.loc[train['age'] > 60]\n",
    "income_working = working_train['MonthlyIncome'].mean()\n",
    "income_retired = retired_train['MonthlyIncome'].mean()\n",
    "income_working, income_retired"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6628.752541914091, 7455.069893679063)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "working_test = test.loc[(test['age'] >= 18) & (test['age'] <= 60)]\n",
    "retired_test = test.loc[test['age'] > 60]\n",
    "income_working = working_test['MonthlyIncome'].mean()\n",
    "income_retired = retired_test['MonthlyIncome'].mean()\n",
    "income_working, income_retired"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出虽然测试集的平均收入相差不多，但是训练集相差较大。用平均值进行空值填充效果可能不佳。接下来查看中位数情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5416.0, 5223.0)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_working = working_train['MonthlyIncome'].median()\n",
    "income_retired = retired_train['MonthlyIncome'].median()\n",
    "income_working, income_retired"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5416.0, 5305.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_working = working_test['MonthlyIncome'].median()\n",
    "income_retired = retired_test['MonthlyIncome'].median()\n",
    "income_working, income_retired"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "两个数据的中位数相差都不大，用中位数进行填列。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['MonthlyIncome'].fillna(train['MonthlyIncome'].median(), inplace = True)\n",
    "test['MonthlyIncome'].fillna(test['MonthlyIncome'].median(), inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来查看家庭成员数目。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 0.0)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train['NumberOfDependents'].median(), test['NumberOfDependents'].median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可见，训练集和测试集的中位数都是0，用中位数填充空值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "train['NumberOfDependents'].fillna(train['NumberOfDependents'].median(), inplace = True)\n",
    "test['NumberOfDependents'].fillna(test['NumberOfDependents'].median(), inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 替换不合理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在数据集分析过程中可以看到，训练集中年龄的最小值为0，而实际情况下借款人必须成年，这对于实际情况来说是不合理的，用平均值进行替换。而用于预测的数据集不存在这样的问题。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.loc[train['age'] < 18, 'age'] = train['age'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在数据集分析中，根据热力图我们可以看到，三个逾期还款的特征之间相关度都很高，且接近1，有可能出现了极端情况。查看这三个特征的箱型图："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (18, 10))\n",
    "train[['NumberOfTime30-59DaysPastDueNotWorse',\n",
    "       'NumberOfTimes90DaysLate',\n",
    "       'NumberOfTime60-89DaysPastDueNotWorse']].boxplot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (18, 10))\n",
    "test[['NumberOfTime30-59DaysPastDueNotWorse',\n",
    "       'NumberOfTimes90DaysLate',\n",
    "       'NumberOfTime60-89DaysPastDueNotWorse']].boxplot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，绝大部分数据都分布在0-20范围内，少部分数据与该范围偏差极大，达到了90以上。我们认为这些数据是不合理的，会不利于模型的构建，因此进行替换，替换为中位数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#替换函数\n",
    "def replace_abnormal(data, feats):\n",
    "    for f in feats:\n",
    "        median = data[f].median()\n",
    "        for i in range(len(data[f])):\n",
    "            if data[f][i] > 90:\n",
    "                data[f][i] = median\n",
    "    return data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "替换训练集中的数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\anac\\lib\\site-packages\\ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "train = replace_abnormal(train, ['NumberOfTime30-59DaysPastDueNotWorse','NumberOfTimes90DaysLate','NumberOfTime60-89DaysPastDueNotWorse'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "替换测试集中的数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\anac\\lib\\site-packages\\ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "test = replace_abnormal(test, ['NumberOfTime30-59DaysPastDueNotWorse','NumberOfTimes90DaysLate','NumberOfTime60-89DaysPastDueNotWorse'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "处理后再查看特征与特征之间的关系："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = train.dtypes[train.dtypes != \"object\"].index\n",
    "features = features.drop('No')\n",
    "#绘制热力图查看特征与特征之间的相关性\n",
    "corr = train[features].corr()\n",
    "plt.figure(figsize=(18, 15))\n",
    "sns.heatmap(corr, annot=True, fmt='.2g', cmap = 'GnBu')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据标准化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先将特征和标签进行分离。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = train.drop(['No', 'SeriousDlqin2yrs'], axis = 1)\n",
    "y = train['SeriousDlqin2yrs']\n",
    "pred = test.drop(['No', 'SeriousDlqin2yrs'], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将数据标准化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler().fit(X)\n",
    "X_scaled = scaler.transform(X)\n",
    "scaler2 = StandardScaler().fit(pred)\n",
    "pred_scaled = scaler.transform(pred)\n",
    "X_scaled = pd.DataFrame(X_scaled, columns = X.columns, index = None)\n",
    "pred_scaled = pd.DataFrame(pred_scaled, columns = pred.columns, index = None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 划分数据集"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以4：1的比例划分训练集和验证集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, random_state=10, test_size = 0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 构建模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "定义绘制ROC曲线的函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_roc_curve(fpr, tpr, label=None):\n",
    "    plt.figure(figsize=(12,10))\n",
    "    plt.plot(fpr, tpr, linewidth=2, label=label)\n",
    "    plt.plot([0,1],[0,1], \"k--\") # 画直线做参考\n",
    "    plt.axis([0,1,0,1])\n",
    "    plt.xlabel(\"False Positive Rate\")\n",
    "    plt.ylabel(\"True Positive rate\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 构建梯度提升决策树模型(lightgbm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lightgbm as lgb\n",
    "from sklearn.metrics import roc_curve, roc_auc_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "class gbm_model():\n",
    "    def __init__(self, X_train, X_test, y_train, y_test, pred):\n",
    "        self.X_train = X_train.astype(float)\n",
    "        self.X_test = X_test.astype(float)\n",
    "        self.y_train = y_train.astype(float)\n",
    "        self.y_test = y_test.astype(float)\n",
    "        self.pred = pred.astype(float)\n",
    "        self.pre_label_train = None\n",
    "        self.pre_label_test = None\n",
    "        self.feature_name = [i for i in self.X_train.columns]\n",
    "        self.lgb_train = lgb.Dataset(data=self.X_train[self.feature_name],\n",
    "                                     label=self.y_train,\n",
    "                                     feature_name=self.feature_name)\n",
    "        self.lgb_test = lgb.Dataset(data=self.X_test[self.feature_name],\n",
    "                                    label=self.y_test,\n",
    "                                    feature_name=self.feature_name)\n",
    "        self.param = self.basic()\n",
    "        self.gbm = None\n",
    "        self.evals_result = {}\n",
    "    \n",
    "    def basic(self):\n",
    "        param = dict()\n",
    "        param['objective'] = 'binary'\n",
    "        param['boosting_type'] = 'gbdt'\n",
    "        param['metric'] = 'auc'\n",
    "        param['verbose'] = 0\n",
    "        param['learning_rate'] = 0.1\n",
    "        param['max_depth'] = -1\n",
    "        param['feature_fraction'] = 0.8\n",
    "        param['bagging_fraction'] = 0.8\n",
    "        param['bagging_freq'] = 1\n",
    "        param['num_leaves'] = 15\n",
    "        param['min_data_in_leaf'] = 64\n",
    "        param['is_unbalance'] = False\n",
    "        param['verbose'] = -1\n",
    "        return param\n",
    "    \n",
    "    def fit(self):\n",
    "        self.gbm = lgb.train(self.param,\n",
    "                             self.lgb_train,\n",
    "                             early_stopping_rounds=10,\n",
    "                             num_boost_round=1000,\n",
    "                             evals_result=self.evals_result,\n",
    "                             valid_sets=[self.lgb_train, self.lgb_test],\n",
    "                             verbose_eval=10)\n",
    "        \n",
    "    def evaluate_train(self):\n",
    "        prob_label = self.gbm.predict(self.X_train[self.feature_name])\n",
    "        auc = roc_auc_score(y_train, prob_label)\n",
    "        self.pre_label_train = np.copy(prob_label)\n",
    "        return auc\n",
    "    \n",
    "    def evaluate_test(self):\n",
    "        prob_label = self.gbm.predict(self.X_test[self.feature_name])\n",
    "        auc = roc_auc_score(y_test, prob_label)\n",
    "        self.pre_label_test = np.copy(prob_label)\n",
    "        return auc\n",
    "    \n",
    "    def save_predict(self):\n",
    "        prob_label = self.gbm.predict(self.pred[self.feature_name])\n",
    "        ids = [i+1 for i in range(self.pred.shape[0])]\n",
    "        ids = np.asarray(ids)\n",
    "        file = pd.DataFrame({'Id': ids, 'Probability': prob_label})\n",
    "        file.to_csv('data' + r'\\result_gbm.csv', index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "训练模型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 10 rounds\n",
      "[10]\ttraining's auc: 0.858871\tvalid_1's auc: 0.863194\n",
      "[20]\ttraining's auc: 0.86289\tvalid_1's auc: 0.866042\n",
      "[30]\ttraining's auc: 0.865921\tvalid_1's auc: 0.868651\n",
      "[40]\ttraining's auc: 0.868133\tvalid_1's auc: 0.869468\n",
      "[50]\ttraining's auc: 0.869803\tvalid_1's auc: 0.870061\n",
      "[60]\ttraining's auc: 0.871787\tvalid_1's auc: 0.870593\n",
      "[70]\ttraining's auc: 0.8731\tvalid_1's auc: 0.870651\n",
      "Early stopping, best iteration is:\n",
      "[61]\ttraining's auc: 0.87193\tvalid_1's auc: 0.870666\n"
     ]
    }
   ],
   "source": [
    "gbm = gbm_model(X_train, X_test, y_train, y_test, pred_scaled)\n",
    "gbm.fit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "绘制训练集ROC曲线并得出AUC值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC score of the training set: 0.8719295960094112\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbm_auc_train = gbm.evaluate_train()\n",
    "fpr_gbm_train, tpr_gbm_train, thresh_gbm_train = roc_curve(y_train, gbm.pre_label_train)\n",
    "plot_roc_curve(fpr_gbm_train, tpr_gbm_train)\n",
    "print(\"AUC score of the training set:\", gbm_auc_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "绘制验证集的ROC曲线并得出AUC值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC score of the testing set: 0.870665729818148\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gbm_auc_test = gbm.evaluate_test()\n",
    "fpr_gbm_test, tpr_gbm_test, thresh_gbm_test = roc_curve(y_test, gbm.pre_label_test)\n",
    "plot_roc_curve(fpr_gbm_test, tpr_gbm_test)\n",
    "print(\"AUC score of the testing set:\", gbm_auc_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由结果可知，训练集和验证集的AUC结果相差不大，说明没有过拟合的问题。AUC值较高，模型效果好。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结果分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们观察各个特征在模型中的重要性。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "定义绘制各特征重要性的函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_feature_importances(importance):\n",
    "    plt.figure(figsize=(10,8))\n",
    "    n_features = X_train.shape[1]\n",
    "    plt.barh(range(n_features), importance, align='center')\n",
    "    plt.yticks(np.arange(n_features), X.columns)\n",
    "    plt.xlabel('Feature importance')\n",
    "    plt.ylabel('Feature')\n",
    "    plt.ylim(-1, n_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### lightgbm模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_feature_importances(gbm.gbm.feature_importance())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可见，在lightgbm模型中，信用卡和个人信贷额度的总余额（不动产、分期付款的债务除外）占信用额度比例和债务比例最为重要。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 评测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "比较三种模型的结果，lightgbm的AUC值最高。保存其结果并提交到kaggle网站上进行评测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "gbm.save_predict()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
